The present invention relates to computer-based systems which provide analysis and query by image content.
Conventional computer systems have been employed to analyze visual images. These visual images include, for example, photographic stills, digitally rendered graphics, video clips, and any other monochrome or color images suitable for representation in a digital system. One goal of these image analysis or image processing systems is to generate information about the characteristics of an image so the image can be classified or used to query an image database.
Conventional image processing techniques include many methods for extracting characteristics or features from an image. For example, techniques are known for extracting color, texture, and component shape characteristics of a given image. The prior art techniques for extracting the color features of an image typically employ one of two methods. First, the user may select a desired color, which is used as the basis for an image color query. Images are matched to the selected color based on the average color of the matched image over the entirety of the image. A second prior art image color analysis technique determines not only the overall color of a desired image, but also the percentage coverage of that color and the compactness of its coverage in a desired image. The percentage color coverage and color compactness are used as additional query conditions in these prior art systems. An example of these conventional techniques is given in E. Binaghi, et al, xe2x80x9cIndexing and Fuzzy Logic-Based Retrieval of Color Imagesxe2x80x9d, Visual Database Systems, II. IFIP Transactions A-7, pp. 79-92, Elsevier Science Publishers, 1992.
Other prior art image analysis techniques are known for extracting texture features of an image. Texture features such as granularity, directionality, and tiling features of a given image can be extracted using known techniques. One example of such techniques is found in H. Tamura, et al, xe2x80x9cTextural Features Corresponding to Visual Perceptionxe2x80x9d, EEE Proceedings, Vol. SMC-8, No. 6, June 1978, pp. 460-473.
Still other techniques are known in the prior art for classifying an image based on structure features, which represent shapes found in the image. Using these known techniques, predefined shapes, such as rectangular, triangular, or circular shapes among others, may be compared to an image to determine the presence of such shapes in the image. This known technique may be used to query an image database for images having a particular specified shape. One example of a prior art method for image analysis based on shapes is found in G. Taubin and D. B. Cooper, xe2x80x9cRecognition and Positioning of Rigid Objects Using Algebraic Moment Invariantsxe2x80x9d, Geometric Methods in Computer Vision, SPIE , Vol. 1570, pp. 175-186, 1992.
Other prior art systems have sought to combine a plurality of image color analysis techniques into a single system. For example, U.S. Pat. No. 5,751,286 describes an image query system and method wherein the visual characteristics of an image such as color, texture, shape, and size are used to develop an image query. The technique described in this patent involves selecting from a plurality of image characteristic selections represented by thumbnail icons corresponding to various image characteristics for a particular image query. As shown in the ""286 patent, these image characteristic (feature) selections are submitted to a query by image content (QBIC) engine, which compares the various image characteristic selections with a database of stored images. Although the ""286 patent describes the technique for processing various types of image characteristics, the described centralized QBIC engine must be capable of handling all of the supported types of image feature processing. As will be discussed in more detail below, the fully supportive QBIC engine has a number of significant drawbacks.
As evident from the prior art describing image-processing techniques, image analysis and image query systems demand a high degree of processing power. In fact, processing even one of the various types of image characteristics, such as color or texture, involves many processor cycles and data storage accesses. An image query system, such as the one described in the ""286 patent, that supports a plurality of image characteristic analysis methods must therefore be a very complex and expensive system to implement. On the other hand, images for a particular application of such a system may be more appropriately analyzed by a particular image characteristic analysis method and much less efficiently analyzed using other image characteristic analysis methods. Thus, it would be advantageous to enable the configuration of an image query system for a particular application. Unfortunately, the prior art, as represented by the techniques illustrated in the ""286 patent, do not enable such a specific configuration given that the QBIC engine is built to handle a full range of image analysis techniques. One problem with this approach is that a user is forced to purchase or program a full-service system even though many of the supported techniques may be underutilized. Further, the system cannot be easily augmented if a new image analysis technique is developed.
It would be advantageous to implement an image query system that is configurable for a particular application. Specifically, it would be advantageous to provide an image query system that supported image analysis techniques most appropriate for the types of images encountered in a particular application. Such a configurable image query system should be modular and extensible so that a user need only purchase or program those image analysis methods most appropriate for the particular application and so new image analysis methods may be easily incorporated into an existing system. The prior art does not disclose such a system.
Some conventional products purport to provide image analysis modularity. Oracle Corporation of Redwood Shores, California developed the image data cartridge component of the Oracle 8 Database. The Oracle 8 image data cartridges object interfaces associate specific data with procedures that can operate on that data. The image procedures provide the means by which the images can be copied, format converted, and processed on demand. In reality, the Oracle 8 image data cartridges merely support various image and graphic file formats rather than supporting a variety of image content analysis techniques.
Thus, a configurable modular image query system supporting modular feature extraction components and modular scoring components is needed.
An image query and storage apparatus and method including a plurality of dynamically linkable feature modules is disclosed. Each of the plurality of feature modules extract a different set of feature information from an input image. The method and apparatus further includes a database coupled to the plurality of feature modules. The database includes storage for the different set of feature information for each of the plurality of feature modules. The method and apparatus support a query by image content of the database of images using the dynamically linked plurality of feature modules. The method and apparatus further includes a plurality of dynamically linkable scoring modules for processing feature specific scoring information generated by the feature modules.